Mark W Onaitis1, Anthony P Furnary2, Andrzej S Kosinski3, Sunghee Kim3, Daniel Boffa4, Betty C Tong3, Patricia Cowper3, Jeffrey P Jacobs5, Cameron D Wright6, Joe B Putnam7, Felix G Fernandez8. 1. Department of Surgery, University of California-San Diego, La Jolla, California. Electronic address: monaitis@ucsd.edu. 2. Department of Surgery, Starr-Wood Cardiac Group, Portland, Oregon. 3. Duke Clinical Research Institute, Duke University, Durham, North Carolina. 4. Department of Surgery, Yale University, New Haven, Connecticut. 5. Department of Surgery, Johns Hopkins All Children's Heart Institute, St. Petersburg, Florida. 6. Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts. 7. Department of Surgery, Baptist MD Anderson Cancer Center, Jacksonville, Florida. 8. Department of Surgery, Emory University, Atlanta, Georgia.
Abstract
BACKGROUND: Prior risk models using the STS General Thoracic Surgery database (STS-GTSD) have been limited to 30-day outcomes. We have now linked STS data to Medicare data and sought to create a risk prediction model for long-term mortality after lung cancer resection in patients older than 65 years. METHODS: The STS-GTSD was linked to Medicare data for lung cancer resections from 2002 to 2013 as previously reported. Successful linkage was performed in 29,899 lung cancer resection patients. Cox proportional hazards modeling was used to create a long-term survival model. Variable selection was performed using statistically significant univariate factors and known clinical predictors of outcome. Calibration was assessed by dividing the cohort into deciles of predicted survival and discrimination assessed with a C-statistic corrected for optimism via 1,000 bootstrap replications. RESULTS: Median age was 73 years (interquartile range, 68 to 78 years), and 48% of the patients were male. Of the 29,094 patients with nonmissing pathologic stage, 69% were stage I, 18% stage II, 11% stage III, and 2% stage IV. Procedure performed was lobectomy in 69%, bilobectomy in 3%, pneumonectomy in 3%, segmentectomy in 7%, sleeve lobectomy in 1%, and wedge resection in 17%. Thoracoscopic approach was performed in 47% of resections. The final Cox model reveals that stage and age are the strongest predictors of long-term survival. Even after controlling for stage, wedge resection, segmentectomy, bilobectomy, and pneumonectomy are all associated with increased hazard of death in comparison with lobectomy. Thoracoscopic approach is associated with improved long-term survival in comparison with thoracotomy. Other modifiable predictive factors include smoking and low body mass index. Calibration of the model demonstrates excellent performance across all survival deciles and a C-statistic of 0.694. CONCLUSIONS: The STS-GTSD-Medicare long-term risk model includes several novel factors associated with mortality. Although medical factors predict long-term survival, age and stage are the strong predictors. Despite this, procedure choice and thoracoscopic/open approach are potentially modifiable predictors of long-term survival after lung cancer resection.
BACKGROUND: Prior risk models using the STS General Thoracic Surgery database (STS-GTSD) have been limited to 30-day outcomes. We have now linked STS data to Medicare data and sought to create a risk prediction model for long-term mortality after lung cancer resection in patients older than 65 years. METHODS: The STS-GTSD was linked to Medicare data for lung cancer resections from 2002 to 2013 as previously reported. Successful linkage was performed in 29,899 lung cancer resection patients. Cox proportional hazards modeling was used to create a long-term survival model. Variable selection was performed using statistically significant univariate factors and known clinical predictors of outcome. Calibration was assessed by dividing the cohort into deciles of predicted survival and discrimination assessed with a C-statistic corrected for optimism via 1,000 bootstrap replications. RESULTS: Median age was 73 years (interquartile range, 68 to 78 years), and 48% of the patients were male. Of the 29,094 patients with nonmissing pathologic stage, 69% were stage I, 18% stage II, 11% stage III, and 2% stage IV. Procedure performed was lobectomy in 69%, bilobectomy in 3%, pneumonectomy in 3%, segmentectomy in 7%, sleeve lobectomy in 1%, and wedge resection in 17%. Thoracoscopic approach was performed in 47% of resections. The final Cox model reveals that stage and age are the strongest predictors of long-term survival. Even after controlling for stage, wedge resection, segmentectomy, bilobectomy, and pneumonectomy are all associated with increased hazard of death in comparison with lobectomy. Thoracoscopic approach is associated with improved long-term survival in comparison with thoracotomy. Other modifiable predictive factors include smoking and low body mass index. Calibration of the model demonstrates excellent performance across all survival deciles and a C-statistic of 0.694. CONCLUSIONS: The STS-GTSD-Medicare long-term risk model includes several novel factors associated with mortality. Although medical factors predict long-term survival, age and stage are the strong predictors. Despite this, procedure choice and thoracoscopic/open approach are potentially modifiable predictors of long-term survival after lung cancer resection.
Authors: Xiayi Lv; Zhigang Wu; Jinlin Cao; Yeji Hu; Kai Liu; Xiaona Dai; Xiaoshuai Yuan; Yiqing Wang; Kui Zhao; Wang Lv; Jian Hu Journal: Transl Lung Cancer Res Date: 2021-01
Authors: Joseph D Phillips; Eleah D Porter; Brendin R Beaulieu-Jones; Kayla A Fay; Rian M Hasson; Timothy M Millington; David J Finley Journal: J Thorac Dis Date: 2020-06 Impact factor: 3.005